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My rough summary of the match, informed by the various commentators and random news stories. Game 1: Lee Sedol does not know what to expect. He plays testing

My rough summary of the match, informed by the various commentators and random news stories. Game 1: Lee Sedol does not know what to expect. He plays testing moves early and gets punished, losing the game decisively. Game 2: Lee Sedol calms down and plays as if he is playing a strong opponent. He plays strong moves waiting for AlphaGo to make a mistake. AlphaGo responds calmly keeping a lead throughout the game. Game 3: Lee Sedol plans a strategy to attack white from the start, but fails. He valiantly plays to the end, creating an interesting position after the game was decided deep in AlphaGo's territory. Game 4: Lee Sedol focuses on territory early on, deciding to replicate his late game invasion from the previous game, but on a larger scale earlier in the game. He wins this game with a brilliant play at move 78. Game 5: The prevailing opinion ahead of the game was that AlphaGo was weak at attacking groups. Lee Sedol crafted an excellent early game to try to exploit that weakness. Tweet from Hassabis midgame [0]: #AlphaGo made a bad mistake early in the game (it didnt know a known tesuji) but now it is trying hard to claw it back... nail-biting. After a back and forth late middlegame, Myungwan Kim 9p felt there were many missed chances that caused Lee Sedol to ultimately lose the game by resignation in the late endgame behind a few points. Ultimately, this match was a momentous occasion for both the AI and the go community. My big curiosity is how much more AlphaGo can improve. Did Lee Sedol find fundamental weaknesses that will continue to crop up regardless of how many CPUs you throw at it? How would AlphaGo fare against opponents with different styles? Perhaps Park Jungwhan, a player with a stronger opening game. Or perhaps Ke Jie, the top ranked player in the world [1], given that they'd have access to the game records of Lee Sedol? I also wonder if the quick succession of these games on an almost back-to-back game schedule played a role in Lee Sedol's loss. Myungwan Kim felt that if Lee Sedol were to play AlphaGo once more, the game would be a coinflip since AlphaGo is likely stronger, but would never fix its weakness between games. [0]: https://twitter.com/demishassabis/status/709635140020871168 https://twitter.com/demishassabis/status/709635140020871168 [1]: http://www.goratings.org/ http://www.goratings.org/

jacobolus 11y ago
Lee Sedol was also coming directly from playing a tournament against human players. It’s not clear how much he prepared for the Alphago match. I’d be very curious to see a game between Lee Sedol and Alphago where each was given 4–5 hours of play time, instead of 2 hours each. I suspect Lee Sedol would get more benefit from spending a longer time reading into moves than Alphago could get. Or even a game where the overtime periods were extended to 4–5 minutes. This last game, Lee spent the whole late middlegame and endgame playing in his 1 minute overtime periods, which doesn’t give much time to carefully compare very complex alternatives.
- awwducks 11y ago
  Yep, I felt the same way. I wonder if the time constraints were optimized for AlphaGo. One of the things I did want to see was how AlphaGo would fare in a blitz situation (i.e. really short timers).
  - frankchn 11y ago
    AlphaGo played 5 informal games with shorter time controls alongside the formal games against Fan Hui (the European champion) back in October. "Time controls for formal games were 1 h main time plus three periods of 30 s byoyomi. Time controls for informal games were three periods of 30 s byoyomi." The games were played back-to-back (formal, then informal) and AlphaGo won 3-2 in the informal games compared to 5-0 in the formal ones, so I would say worse.
    - jacobolus 11y ago
      The question is whether Alphago’s architecture starts hitting diminishing returns to extra processing faster than top humans is a significantly different question from whether it scales down to a blitz game worse. (Moreover, the difference between 1h main time + 3x 30s byoyomi vs. only 3x 30s byoyomi is absolutely massive.) Deepmind engineers have stated that the “cluster” version of Alphago only beats the “single machine” version about 70% of the time. This despite the cluster version using like an order of magnitude more compute resources, presumably able to search several moves deeper in the full search tree. My impression is that there are some fundamental weaknesses in the (as currently trained and implemented) value network, which Lee Sedol was able to exploit. If this is the case, giving the computer time to cover an extra move or two of search depth might not make a huge difference. Giving Lee Sedol twice as much time, however, would have had a significant impact on several of the games in this series, especially the last game. I strongly suspect that with a few extra minutes per move Lee Sedol would have avoided the poor trades in the late-midgame which cost him the game.
  - hosh 11y ago
    I think the DeepMind team might not even have thought deeply about time control. If we were to express this with the known systems in AlphaGo, how do we express the idea that a surprising move should be given more thought? For example, match 4, move 78 was calculated by AlphaGo as having a probability of being played at 1 in 10,000. Is that something that could trigger a deeper read and use of more time? Another thing that the commentator was talking about during the the overtime: there would be obvious moves in which Lee Sedol seem to spend a lot of time on. But he was spending most of it thinking of other moves having already decided on what he was going to do. Is that something that could be built into AlphaGo? Or can we look at how to train a net for time control? Is time control something that has to be wired in?
zamalek 11y ago
> Lee Sedol focuses on territory early on I get the feeling that this was AlphaGo's strategy in all the games. Unless Sedol presented a game-ending move it was overwhelmingly likely that AlphaGo would back down and focus elsewhere to extend its territory, by making non-aggressive defensive moves. This makes logical sense. During the early game you need to invoke a crystal ball, where during the endgame you can make informed decisions. This was demonstrated particularly well during game 3 where AlphaGo ran away from fights on numerous occasions - "leave me alone to extend my territory." I must also commend the commentators, especially Redmond, for being so thoroughly informative in unknown waters.
Razengan 11y ago
> Did Lee Sedol find fundamental weaknesses that will continue to crop up regardless of how many CPUs you throw at it? Unrelated to Go and this article, but I wonder if I'm the only one for whom such commentary evokes an image of future warfare between AI and humans; ruthlessly efficient machines against which many people give their lives, to find a weakness that can be exploited by future generations. :)
- visarga 11y ago
  I think the ruthlessly efficient machines will find the smart yet efficient human brains more useful to keep around than to destroy. We'll probably augment ourselves with AI and AI will work better in partnership with us.
  - ams6110 11y ago
    That's pretty optimistic, or arrogant. Not sure which. But it doesn't really comport with biological history.
    - anotheryou 11y ago
      For a while the co-evolution makes most sense I think. Right now we have augmented intelligence with all our tech, it will just grow from outside our bodies loser connected to the inside.
      - pixl97 11y ago
        co-evolution makes sense right until the point right until the point where one becomes dominant and the other becomes a parasite. That said, our bodies still have things that are practically different life forms integrated into our cells, so maybe the future will be far weirder than we ever expected.
    - meric 11y ago
      It's fair to expect too - these days AI can't exist without human beings, so I guess if someone is extrapolating AI in the future, it's instinct to use the present as baseline.

jacobolus 11y ago

Lee Sedol was also coming directly from playing a tournament against human players. It’s not clear how much he prepared for the Alphago match. I’d be very curious to see a game between Lee Sedol and Alphago where each was given 4–5 hours of play time, instead of 2 hours each. I suspect Lee Sedol would get more benefit from spending a longer time reading into moves than Alphago could get. Or even a game where the overtime periods were extended to 4–5 minutes. This last game, Lee spent the whole late middlegame and endgame playing in his 1 minute overtime periods, which doesn’t give much time to carefully compare very complex alternatives.

awwducks 11y ago
Yep, I felt the same way. I wonder if the time constraints were optimized for AlphaGo. One of the things I did want to see was how AlphaGo would fare in a blitz situation (i.e. really short timers).
- frankchn 11y ago
  AlphaGo played 5 informal games with shorter time controls alongside the formal games against Fan Hui (the European champion) back in October. "Time controls for formal games were 1 h main time plus three periods of 30 s byoyomi. Time controls for informal games were three periods of 30 s byoyomi." The games were played back-to-back (formal, then informal) and AlphaGo won 3-2 in the informal games compared to 5-0 in the formal ones, so I would say worse.
  - jacobolus 11y ago
    The question is whether Alphago’s architecture starts hitting diminishing returns to extra processing faster than top humans is a significantly different question from whether it scales down to a blitz game worse. (Moreover, the difference between 1h main time + 3x 30s byoyomi vs. only 3x 30s byoyomi is absolutely massive.) Deepmind engineers have stated that the “cluster” version of Alphago only beats the “single machine” version about 70% of the time. This despite the cluster version using like an order of magnitude more compute resources, presumably able to search several moves deeper in the full search tree. My impression is that there are some fundamental weaknesses in the (as currently trained and implemented) value network, which Lee Sedol was able to exploit. If this is the case, giving the computer time to cover an extra move or two of search depth might not make a huge difference. Giving Lee Sedol twice as much time, however, would have had a significant impact on several of the games in this series, especially the last game. I strongly suspect that with a few extra minutes per move Lee Sedol would have avoided the poor trades in the late-midgame which cost him the game.
- hosh 11y ago
  I think the DeepMind team might not even have thought deeply about time control. If we were to express this with the known systems in AlphaGo, how do we express the idea that a surprising move should be given more thought? For example, match 4, move 78 was calculated by AlphaGo as having a probability of being played at 1 in 10,000. Is that something that could trigger a deeper read and use of more time? Another thing that the commentator was talking about during the the overtime: there would be obvious moves in which Lee Sedol seem to spend a lot of time on. But he was spending most of it thinking of other moves having already decided on what he was going to do. Is that something that could be built into AlphaGo? Or can we look at how to train a net for time control? Is time control something that has to be wired in?

zamalek 11y ago

> Lee Sedol focuses on territory early on I get the feeling that this was AlphaGo's strategy in all the games. Unless Sedol presented a game-ending move it was overwhelmingly likely that AlphaGo would back down and focus elsewhere to extend its territory, by making non-aggressive defensive moves. This makes logical sense. During the early game you need to invoke a crystal ball, where during the endgame you can make informed decisions. This was demonstrated particularly well during game 3 where AlphaGo ran away from fights on numerous occasions - "leave me alone to extend my territory." I must also commend the commentators, especially Redmond, for being so thoroughly informative in unknown waters.

Razengan 11y ago

> Did Lee Sedol find fundamental weaknesses that will continue to crop up regardless of how many CPUs you throw at it? Unrelated to Go and this article, but I wonder if I'm the only one for whom such commentary evokes an image of future warfare between AI and humans; ruthlessly efficient machines against which many people give their lives, to find a weakness that can be exploited by future generations. :)

visarga 11y ago
I think the ruthlessly efficient machines will find the smart yet efficient human brains more useful to keep around than to destroy. We'll probably augment ourselves with AI and AI will work better in partnership with us.
- ams6110 11y ago
  That's pretty optimistic, or arrogant. Not sure which. But it doesn't really comport with biological history.
  - anotheryou 11y ago
    For a while the co-evolution makes most sense I think. Right now we have augmented intelligence with all our tech, it will just grow from outside our bodies loser connected to the inside.
    - pixl97 11y ago
      co-evolution makes sense right until the point right until the point where one becomes dominant and the other becomes a parasite. That said, our bodies still have things that are practically different life forms integrated into our cells, so maybe the future will be far weirder than we ever expected.
  - meric 11y ago
    It's fair to expect too - these days AI can't exist without human beings, so I guess if someone is extrapolating AI in the future, it's instinct to use the present as baseline.